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Financial Analysts' Forecasts and Stock Recommendations

Financial Analysts' Forecasts and Stock Recommendations
Author: Sundaresh Ramnath
Publisher: Now Publishers Inc
Total Pages: 125
Release: 2008
Genre: Business & Economics
ISBN: 1601981627

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Financial Analysts' Forecasts and Stock Recommendations reviews research related to the role of financial analysts in the allocation of resources in capital markets. The authors provide an organized look at the literature, with particular attention to important questions that remain open for further research. They focus research related to analysts' decision processes and the usefulness of their forecasts and stock recommendations. Some of the major surveys were published in the early 1990's and since then no less than 250 papers related to financial analysts have appeared in the nine major research journals that we used to launch our review of the literature. The research has evolved from descriptions of the statistical properties of analysts' forecasts to investigations of the incentives and decision processes that give rise to those properties. However, in spite of this broader focus, much of analysts' decision processes and the market's mechanism of drawing a useful consensus from the combination of individual analysts' decisions remain hidden in a black box. What do we know about the relevant valuation metrics and the mechanism by which analysts and investors translate forecasts into present equity values? What do we know about the heuristics relied upon by analysts and the market and the appropriateness of their use? Financial Analysts' Forecasts and Stock Recommendations examines these and other questions and concludes by highlighting area for future research.


Two Essays in Financial Accounting

Two Essays in Financial Accounting
Author: Dorothy Alexander-Smith
Publisher:
Total Pages: 143
Release: 2011
Genre: Business forecasting
ISBN:

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Essay 1: The Association of Earnings Quality with Financial Analysts' Earnings Forecast Attributes. This study investigates the association between firms' earnings quality and analysts' forecast errors and dispersion. The findings suggest that the quality of earnings is inversely related to analysts' forecast errors but is not associated with forecast dispersion. These results are better understood by an examination of the relationship of forecast error and dispersion with the major sub-components of earnings quality- the quality of the innate accrual component (quality of accruals related to the complexity of the firm's operations) and the quality of the discretionary accrual component (quality of managements' judgment as reflected in accruals used to project future performance). The inverse association between earnings quality and forecast error is driven primarily by the quality of the firm's innate accrual component (InnAQ). As firm complexity and variability increase, earnings contain larger amounts of management judgment and estimation. The larger amount of management estimation included in earnings renders it relatively less reliable and thus forecasting difficulty (reflected in greater forecast errors and dispersion) is amplified for poorer InnAQ. This inverse association is the dominant effect in earnings quality's association with analysts' forecast errors. The quality of firms' discretionary accrual components depends upon whether managers use of their discretion to provide value relevant information, or whether they use the discretionary component to incorporate manipulative and noisy discretionary accruals. In a regression of the of firms' discretionary earnings components on forecast dispersion I find an inverse relationship between the magnitude of the firm's discretionary earnings component and analysts' forecast dispersion. This is consistent with managers using the discretionary component to provide information on firm performance, thus facilitating more precision in analysts' forecasts. This essay contributes to two controversial areas of accounting research. The study indirectly provides evidence supporting managers' (on average) use of their discretion to provide value relevant information in earnings; and it simultaneously demonstrates analysts' expertise in incorporating information related to EQ and its sub components into their forecasts. Essay 2: The Influence of Earnings Quality on Financial Analysts' Herding Behavior. Essay 2 investigates how firms' EQ and its innate (the quality of accruals related to the complexity of the firm's operations) and discretionary (the quality of accruals based on managements' discretion) sub-components affect analysts' motivation to issue herding forecasts. Herding forecasts are forecasts which mimic those issued by other analysts and ignore the analyst's own private information. Although theoretical studies have linked herding behavior to analysts' rational reputational concerns, herding reduces the information available to investors in the market and hence negatively impacts market efficiency. Conversely, bold forecasts, forecasts issued which move away from the consensus (linked in prior studies to greater private information release and higher accuracy) are likely to contribute to improved market efficiency. As capital market intermediaries, financial analysts are charged with facilitating investors' investment decisions. The literature documents that poor earnings quality reduces investors' ability to evaluate firm performance. This essay contributes to the literature by providing evidence on how financial analysts' herding behavior is influenced by EQ and its sub components. Results show that the quality of the firm's innate accrual component is the major driver of analysts' bold forecasting. The negative association between forecast boldness and firms' innate accrual quality indicates that analysts issue bolder forecasts when investors have more difficulty determining firm value (noisier signal from innate accrual component). Given the prior literature finds that bolder forecasts contain more private information and are more accurate, the results suggests that analysts are effectively performing their market intermediary function. The lack of a significant association between bold forecasting and the discretionary earnings component is in line with prior literature's documentation of analysts' poor utilization of the discretionary information in their forecasts. However, this study's evidence of a positive association between bold forecasts and analysts' firm specific experience implies that analysts with more firm specific experience have a greater understanding of managers' discretionary signals and exploit their advantage by issuing bolder forecasts. Results show a negative association between firms' overall EQ and analysts' forecast boldness implying that analysts herd more the higher the firm's EQ. This finding underscores the importance of reputational concerns and the demand for analysts' investment advice for analysts' herding behavior.


Audit Quality and Properties of Analyst Earnings Forecasts

Audit Quality and Properties of Analyst Earnings Forecasts
Author: Bruce K. Behn
Publisher:
Total Pages:
Release: 2008
Genre:
ISBN:

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Under the assumption that audit quality relates positively to unobservable financial reporting reliability, we investigate whether audit quality is associated with the predictability of accounting earnings by focusing on analyst earnings forecast properties. The evidence shows that analysts' earnings forecast accuracy is higher and the forecast dispersion is smaller for firms audited by a Big Five auditor. We further find that auditor industry specialization is associated with higher forecast accuracy and less forecast dispersion in the non-Big Five auditor sample but not in the Big Five auditor sample. Overall, our results suggest that high quality audit provided by Big Five auditors and industry specialist non-Big Five auditors is associated with better forecasting performance by analysts.


The Effect of Earnings Quality on Analyst Forecast Accuracy, Dispersion, and Optimism and Implications for CEO Compensation

The Effect of Earnings Quality on Analyst Forecast Accuracy, Dispersion, and Optimism and Implications for CEO Compensation
Author: David F. Salerno
Publisher:
Total Pages: 153
Release: 2013
Genre: Chief executive officers
ISBN:

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Extant research indicates that earnings attributes are important considerations to corporate decision makers and users of accounting information (e.g., Francis et al., 2004). One such attribute is earnings quality; often measured as the magnitude of accruals that do not convert to cash in a timely manner, where a poor match of cash flows and accruals indicates low earnings quality (e.g., Dechow and Dichev, 2002). Such accruals could be used to manage earnings, a practice that aims to achieve a pre-determined level of earnings by using accounting techniques rather than actual firm performance. This study consists of two essays and examines the effect of earnings quality on two groups of financial statement users; specifically financial analysts and CEO compensation setters. The first essay investigates the impact of earnings quality on earnings forecast accuracy, forecast dispersion, and forecast optimism of individual financial analysts. The primary model employed for analyst forecast accuracy is consistent with Barniv et al. (2005), Clement (1999), and Jacob et al. (1999). Further reduced model of forecast accuracy based on variables used by Bae et al. (2008) is also used. The forecast dispersion model is based on that of Behn (2008), and forecast optimism is measured following Cowen et al. (2006). The findings show that when earnings quality is higher, analyst forecasts exhibit greater accuracy and lower optimism. Higher earnings quality has some impact on forecast dispersion; however the affect largely disappears when correcting for correlation within firm clusters. The second essay examines whether earnings quality plays a role in CEO compensation when corporate earnings satisfy (or fail to satisfy) the market's expectations. Specifically, Essay II examines CEO bonus as the measure of compensation used to reward the CEO for performance. Because such rewards are often accomplished with cash compensation, and because salary is usually set before the start of the year, the bonus portion of the CEO's total pay package is likely to be affected by earnings quality (Matsunaga and Park (2001). The results provide evidence that lower earnings quality is associated with higher CEO bonus compensation for firms that have satisfied market earnings expectations.


Factors Affecting the Accuracy of Analysts' Forecasts

Factors Affecting the Accuracy of Analysts' Forecasts
Author: Jahidur Md Rahman
Publisher:
Total Pages: 18
Release: 2020
Genre:
ISBN:

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This study conducts a comprehensive review of the literature published during 1996- 2017 to identify the factors that affect the accuracy of financial analysts' forecasts. We organize our review around three main groups, namely, (a) drivers of analyst forecast accuracy, (b) quality financial reporting, and (c) accounting standards. Among the several factors found, some factors (experience of the analyst, earnings quality, audit quality, IFRS adoption, and annual report readability) have a positive relationship with the accuracy of analysts' forecasts while others (politically connected firms, firms audited by Non-Big 4, and international GAAP differences) have a negative relationship. Our findings contribute to future research by examining the factors affecting analyst forecast accuracy from different perspectives, which will prove to be useful for academicians, regulators, investors, and financial analysts.


Dispersion in Analysts' Forecasts

Dispersion in Analysts' Forecasts
Author: Davit Adut
Publisher:
Total Pages:
Release: 2003
Genre:
ISBN:

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Financial analysts are an important group of information intermediaries in the capital markets. Their reports, including both earnings forecasts and stock recommendations, are widely transmitted and have a significant impact on stock prices (Womack 1996; Lys and Sohn 1990, among others). Empirical accounting research frequently relies on analysts' forecasts to construct proxies for variables of interest. For example, the error in mean forecast is used as a proxy for earnings surprise (e.g., Brown et al. 1987; Wiedman 1996; Bamber et al. 1997). More recent papers provide evidence that the mean consensus forecast is used as a benchmark for evaluating firm performance. (Degeorge et al. 1999; Kasznik and McNichols 2002; Lopez and Rees 2002). Another stream of research uses the forecast dispersion as a proxy for the uncertainty or the degree of consensus among analysts and focuses on the information properties of analysts (e.g., Daley et al. 1988; Ziebart 1990; Imhoff and Lobo 1992; Lang and Lundholm 1996; Barron and Stuerke 1998; Barron et al. 1998). In this paper I combine the two streams of research, and investigate how lack of consensus changes the information environment of analysts and whether the markets perceive this change. More specifically, I investigate the amount of private information in a divergent earnings estimate (i.e. one that is above or below the consensus), whether the markets react to it at either the time of the forecast release, at the realization of actual earnings, and whether Regulation Fair Disclosure has changed the information environment differently for high and low dispersion firms.


Analysts' Forecasts as Earnings Expectations (Classic Reprint)

Analysts' Forecasts as Earnings Expectations (Classic Reprint)
Author: Patricia C. O'Brien
Publisher: Forgotten Books
Total Pages: 134
Release: 2018-03-07
Genre: Mathematics
ISBN: 9780364062012

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Excerpt from Analysts' Forecasts as Earnings Expectations A third contribution of this paper is a methodological refinement of the techniques used to evaluate forecastsp I demonstrate the existence of significant time-period - specific effects in forecast errors. If time series and cross-section data are pooled without taking these effects into account, the statistical results may be overstated, and the results are subject to an aggregation bias. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.